What AI search is, in one paragraph
AI search means a product reads several web pages for you and writes one answer, instead of showing ten links. Showing up means being one of the pages it reads or one of the businesses it names.
The main surfaces today are Google's AI Overviews, which sit above the normal results, and Google's AI Mode, a full conversational search. Alongside them are ChatGPT search, Perplexity, and Microsoft Copilot. Each combines a search step with a writing step. They differ in which index they search, how much they show their sources, and how quickly a change on your site reaches them.
This page is the overview. It explains what each surface reads, what they all share, and a short order of work. It does not go deep on any one engine. For that, follow the links: how to rank in ChatGPT for the OpenAI mechanics, and how to rank in AI Overviews for Google.
If you want the plain-language definition of the Google feature first, our glossary has one for AI Overviews. Everything below assumes you want the practical steps, in order, with no jargon you have to look up.
What each surface reads before it answers
Every AI search surface starts from a search index, but they use different ones and weigh sources differently. Knowing which is which tells you where to put your effort.
Google's AI Overviews and AI Mode draw on Google's own index and its ranking signals. A page that is well indexed, clear and trusted by Google's usual measures has a better chance of being used. Google can also expand one question into several related searches behind the scenes and combine the results, so a page that answers a specific side question can be pulled in even if it does not rank for the main phrase.
ChatGPT search relies on a web search step that includes Bing results among its sources, then reads a few pages and quotes passages. Copilot is built on Bing directly. Perplexity runs its own retrieval and shows its sources prominently next to the answer, which makes it the easiest place to see what was read.
The diagram groups them by behavior. Surfaces tied closely to an index move when your standing in that index moves. Surfaces that retrieve live can reflect an edit sooner, because they fetch pages at question time. Neither group answers from your site alone. They all read other pages about you too.
The foundation they all share
Four things are true for every AI search surface: they must be able to fetch you, understand you, trust you and find you in an index. Fix those before anything engine-specific.
Be fetchable
Check robots.txt and any firewall for rules that block AI crawlers, and make sure your text is in the page itself rather than only drawn by scripts after load. A page that arrives empty to a crawler is invisible to every surface at once.
Be understandable
Lead each page and each section with a plain sentence that answers the question. Use the customer's words. Add schema markup where it fits, such as business details and FAQs, so the facts are machine-readable and consistent.
Be trustworthy
Independent pages describing you, and reviews that name the service, tell every surface that someone besides you stands behind the claim.
Be in the index
Submit sitemaps to Google Search Console and Bing Webmaster Tools. If you are not indexed, you are not a candidate.
If you want those four turned into a sequence with a monthly check, our guide to getting recommended by AI lays out the five steps.
A short order of work
Do the cheap, binary checks first and the slow, reputation-building work in parallel. Here is a sensible order for a small team.
Week one: access and indexing. Audit robots.txt and firewall rules. Verify your site in both Google and Bing webmaster tools and submit sitemaps. Confirm key pages render their text without scripts. This work is short and removes the biggest silent blockers.
Weeks two to four: rewrite the pages that matter. Pick your five most important service or product pages. Rewrite the opening of each so the first sentence states the job, the place and the audience. Add a short question-and-answer section covering the follow-ups customers ask. Fix inconsistent business details across your site and listings.
Ongoing: evidence from outside. Ask every customer for a review that says what you did. Look at which outside sites keep showing up for your category, and earn real mentions on them. This is the slow lever and the one that separates winners from the merely readable. Our guide to what AI engines cite helps you pick targets.
Monthly: measure. Ask the same questions on the same surfaces and write down who is named.
Where the engines differ in practice
The same page can win in one engine and be absent from another, so measure each one separately. There are a few differences worth planning around.
Speed of change. A live-retrieval surface can pick up a rewritten page within days. A surface tied to a search index follows how quickly that index recrawls and reweights your page, which can take weeks. Do not judge all of them on the same schedule.
Source visibility. Perplexity shows a numbered list of sources by default, so you can see exactly who it used. Google's AI features show links alongside or inside the summary. ChatGPT shows sources when it searched. Where sources are visible, you can learn from the winners. Where they are not, you only see the names.
Local and shopping questions. For "near me" questions, Google leans on its business profile data, so an accurate, complete Google Business Profile matters more there than on any other surface. For product questions, merchant feeds and product pages carry weight.
Sampling. Every engine can answer the same question differently on different days. Our page on why AI answers change explains why one reading is never enough.
Show up in Google first if you can only pick one
If your time is short, put the first effort into Google, because its AI features sit on top of the largest search audience. That is a priority call, not a claim that other engines do not matter.
Google's AI Overviews appear above the usual results for many questions, and the pages they cite tend to be pages that already do reasonably well in normal search. That means a lot of what helps traditional search, a clear page, a trusted site, helpful content and good internal links, also helps here. This is a reason to see classic search work and AI work as one body of work, not two competing projects.
Then widen out. Bing indexing carries Copilot and feeds ChatGPT search. Crawler access for OpenAI and Perplexity costs almost nothing to set up. Reviews and outside mentions help everywhere.
If you want to watch what Google is doing with your pages specifically, read tracking AI Overviews. It covers what you can and cannot see for the Google features.
Whichever surface you start with, the work compounds. A page that states its answer plainly, is indexed everywhere, and is backed by outside sources is a candidate on all of them.
Match one page to one buyer question
AI search answers specific questions, so each important page should be the clear answer to one question a buyer really asks. A page that tries to answer everything is a weak match for anything.
Start by listing the questions that lead to a purchase or a call in your business. A dentist might list "how much does a crown cost without insurance," "does a root canal hurt," and "who does same-day emergency appointments near me." A store selling hiking boots might list "what boots for wide feet," "how to break in leather boots" and "waterproof or not for a three-day trek."
Next, check which of your pages answers each one in its first two sentences. Where you find a match, tighten it. Where you find none, write the page. Where you find several pages competing for one question, merge them, because a visitor and a model both do better with one strong page than three weak ones.
Finally, link the pages to each other with descriptive anchor text, so the relationship between "root canal pain" and "crown cost" is plain to a reader and a crawler. The same thinking applies if you build your pages around the way people word things rather than single keywords, which we cover in query clusters versus keyword targeting.
A good test is to read the first two sentences of the page aloud and ask whether a stranger would feel their question was answered. If yes, a model can quote it. If you had to scroll to find the point, so would the model.
What to measure on each surface
Track whether you are named, which sources were used and what the answer says about you, separately for each surface. Blending them hides where you are strong and where you are missing.
For Google's AI features, use Search Console to watch impressions and clicks for the question-style queries you care about, and check by hand whether an Overview appears and whether you are cited in it. For ChatGPT and Perplexity, run your fixed question set and record the businesses and links in each answer. For Copilot, do the same, and also confirm Bing indexing in Bing Webmaster Tools.
Keep three columns for every question on every surface: were you named, who else was named, and the exact sentence used about you. The sentence is the one people skip and the one that matters. Being named as "a cheaper option" and being named as "the specialist for this job" are not the same result.
Re-run monthly and compare like with like. If one surface improves while another does not, look at what separates them in the checklist above, such as crawler access or index coverage, before changing your content.
For a deeper treatment of choosing what to measure and how often, our guide to choosing an AI share of voice tool covers the criteria.
Common mistakes when trying to show up
The most common mistake is treating each AI surface as a separate project when the foundation is shared. Here are the others.
Optimizing only the homepage. Questions are specific, so the page that matches a specific question wins. A single broad homepage rarely does.
Blocking crawlers by accident. A security setting installed years ago can still be turning away every AI crawler today. It takes minutes to check.
Writing for the model instead of the reader. Pages stuffed with phrasing meant to please an AI read badly to people, who are the ones who call you. Clear writing for a customer is also clear to a model.
Ignoring outside evidence. Your own claims are leads, not endorsements. Without independent sources, you look unverified.
Judging on one answer. A single check, good or bad, is noise. Use a fixed question set, as we describe in building an AI visibility question set.
Buying a promise. Any seller guaranteeing a spot in AI answers is guaranteeing something nobody controls. The honest offer is work and measurement.
How RunOctopus handles this
RunOctopus is a done-for-you service. Its AI, Ollie, researches a business and then writes and publishes pages straight onto the business's own website, with a team that plans, writes, reviews and publishes alongside it. It works with Shopify, WordPress, WooCommerce and Wix.
That addresses the on-site half of this guide for every surface at once: answer-first pages, the follow-up questions covered, and the internal links between them. Nothing to install, approve, upload or schedule. In the first week you get 8 long-form articles, 6 pages and a custom interactive tool built for your niche, and after that 175+ pieces of content a month, written, published and linked.
It also reports on where ChatGPT, Perplexity, Claude and Gemini name your business, so you can see the engines separately rather than guess. The 90-day promise is more visibility on Google and in AI answers within 90 days, measured against the 90 days before you joined, or every dollar back.
You can see where your site stands today with a free site read at app.runoctopus.com/start. Paste your address and Ollie reads the site and shows the plan. No account, no call.